1. Field of the Invention
This invention relates to biometric identification through iris recognition, and more specifically to the use of hyper-spectral signatures to distinguish color signatures that are not visually distinguishable in RGB color space.
2. Description of the Related Art
The use of biometric indicia for identification purposes requires that a particular biometric factor be unique for each individual, that it be readily measured, and that it be invariant over time. Although many indicia have been proposed over the years, fingerprints are perhaps the most familiar example of a successful biometric identification scheme. As is well known, no two fingerprints are the same, and they do not change except through injury or surgery. It is equally clear, however, that identification through fingerprints suffers from the significant drawback of requiring physical contact with the person. No method exists for obtaining a fingerprint from a distance.
A biometric indicator that has gained popularity in the last decade is the iris. The iris of every human eye has unique texture features of high complexity, which prove to be essentially immutable over a person's life. No two irises are identical in texture or detail, even in the same person. The spatial diversity of the iris reflected in the texture features can be used as a unique biometric indicator. As an internal organ of the eye the iris is well protected from the external environment, yet it is easily visible even from yards away as a colored disk, behind the clear protective window of the eye's cornea, surrounded by the white tissue (“sclera”) of the eye. Although the iris stretches and contracts to adjust the size of the pupil in response to light, its detailed texture remains largely unaltered apart from stretching and shrinking. Such distortions in the texture can readily be reversed mathematically in analyzing an iris image, to extract and encode an iris signature that remains the same over a wide range of pupillary dilations. The richness, uniqueness, and immutability of iris texture, as well as its external visibility, make the iris suitable for automated and highly reliable personal identification. The registration and identification of the iris can be performed using a video camera without any physical contact, automatically and unobtrusively.
The first attempt to take advantage of these favorable characteristics of the iris for a personal identification system is seen in U.S. Pat. No. 4,641,349 issued to Flom and Safir and entitled “Iris Recognition System.” It has been discovered that every iris is unique, particularly in the detailed structure of the front or anterior layer. Flom extracted a number of structural features including pigment-related features such as frill, collarette, concentric furrow, radial furrow, crypt, pigment spot, atrophic area, tumor, contenital filament etc. and compared these to features stored for identified persons. At col 13, lines 41 to 45, the color could be found by an algorithm obtaining a histogram in three-dimensional RGB color space. The peak in the histogram will provide a descriptor of color.
U.S. Pat. No. 5,291,560 issued to Daugman and entitled “Biometric personal identification system based on iris analysis”, which is hereby incorporated by reference, extended the general concept of iris recognition to a complete and automated system. Image analysis algorithms find the iris in a live video image of a person's face, and encode its texture into a compact signature, or “iris code.” Iris texture is extracted from the monochrome image at multiple scales of analysis by a self-similar set of quadrature (2-D Gabor) bandpass filters defined in a dimensionless polar coordinate system. The original iris image may consist of a 512×512 array of pixels. The sign of the projection of many different parts of the iris onto these multi-scale quadrature filters, determines each bit in an abstract (256-byte) iris code. The degrees-of-freedom in this code are based on the principle forms of variation in a population of irises studied. Because of the universal mathematical format and constant length of the iris codes, comparisons between them are readily implemented by the Exclusive-OR (XOR) logical operation. Pattern recognition is achieved by combining special signal processing methods with statistical decision theory, leading to a statistical test of independence based on a similarity metric (the Hamming distance) that is computed from the XOR of any two iris codes. This measure positively establishes, confirms, or disconfirms, the identity of any individual. It also generates an objective confidence level associated with any such identification decision.
Iris recognition systems in use today are based on Daugman's texture analysis. The earliest systems require the person to put their face up to a scanner. More recent systems use a wall mounted scanner that require the user to simply look up. Customers would like to field systems that can perform iris recognition at ranges beyond 25 meters and perhaps beyond 100 meters. However, at these ranges the sensor resolution and aperture sizes required to provide the spatial resolution for texture analysis are impractical. Texture analysis is diffraction limited, which requires large apertures, and even using arbitrarily large apertures is reaching the limits imposed by Earth atmosphere.